Feature emphasis and de-emphasis are common image processing operations. A feature in an image can be as straightforward as an edge or as complicated as a complex fractal pattern. Image sharpening is one example of feature emphasis. Image smoothing is an example of the opposite process, feature de-emphasis.
One purpose of emphasizing a feature may be to make the image look better or to explicitly exaggerate the feature. A useful application of feature emphasis is edge enhancement. A useful application of feature de-emphasis is noise suppression. Sharpening an image may be required for several reasons. An image that was sharp at its native resolution can often lack sharpness once it has been enlarged, so that sharpening may be needed after enlargement. Alternatively, perceived image sharpness is also a function of the observer's physical distance from the screen. In order to make an image appear adequately sharp, one must be cognizant of the observer's position relative to the screen. Whatever the reason, it is of fundamental importance to be able to adjust the level of sharpness in an image to make it perceptually pleasing.
There are many approaches to feature emphasis and de-emphasis. Of the many ways to perform some sort of feature enhancement, image sharpening is among them. Sharpening algorithms typically perform some sort of edge manipulation. Many approaches, however, are linear methods. Linear approaches to sharpening are fraught with problems. For instance, a constant poly-phase finite impulse response (FIR) filter will act the same way on all image content, so it will exacerbate noise as well as make edges more “sharp.” But so-called sharpening linear filters—those that have some gain in the frequency mid-band—also come with another often unwanted side-effect—Gibb's phenomenon, which is more commonly referred to as ringing. The performance of linear filters that sharpen is particularly poor in regions of the image where there is relatively little content, that is, areas of the image that are very flat. In these regions a sharpening filter only serves to enhance noise. While some overshoot and undershoot is necessary to create an effect that sharpens an image, when ringing occurs, there are many repetitive artifacts close to an edge that are visually unappealing.
It would therefore be desirable to have a feature emphasis/de-emphasis circuit that operates in accordance with the following principles. Such a circuit: 1) should not aggravate areas when the feature is not present; 2) should identify the feature in question; 3) should not alter the feature's fundamental properties, e.g., the size of the feature, although such a circuit may alter the feature's range, i.e., contrast; and 4) should not contain heuristic components. In the more specific context of image sharpening, such a circuit or process should: 1) be benign in regions that are flat or relatively flat; 2) add overshoot and undershoot (emphasis and de-emphasis) in a controlled fashion; 3) not ring; and, 4) not contain any arbitrary user-defined thresholds. Depending on the exact nature of the emphasis/de-emphasis problem, these principles may assume a more specific connotation.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with some aspects of the present invention as set forth in the remainder of the present application with reference to the drawings.